You may be wondering about the title of this post. I’ve decided to reject John Zachman, a non-businessman completely, and name my discovery to honor someone I respect much more highly, an archetypical businessman, Peter Drucker.

The first thing to do is abandon the term “hierarchy”. You are working with networks. You are also dealing with seven networks, not one. This means you are dealing with not seven by seven (49) but seven to the power of seven (over 800,000) nodes in the business space. This is called a seven dimensional hypercube. The main difference between the associative model and the relational model is that the associative (node-link) business area grows into the space while the relational (relation-inferred relationship) business area has to be completely defined. When you are talking about almost one million cells in the schema alone the traditional relational model with all of its NULL values for unused space in tables becomes quite cumbersome. The SQL is resource intensive in both models.

Another thing to abandon is your language. Lay English is often imprecise and inconsistent. I am creating a taxonomy as part of this work to provide a seven dimensional vocabulary. Every one of the terms was thoroughly examined for its definition.

Finally, abandon preconceptions. Look at the data and let it guide you.

There are key levels of abstraction: The schema which are entities and entity associations and instance and instance association. I highly recommend going to Simon William’s site lazysoft.com and reading some of his short white papers on the architecture.

Associations and Entities

A chart of associations is below:

Let’s look at these associations in the context of physics and business:

It is based on an associative (node and link) architecture not a relational (table and relationships) architecture.

Seven Nodes, Six Dimensions

After considerable struggle with the data it became clear to me that I was not dealing with a table in the normal sense. I could not reconcile a data cube with the seven dimensions I had discovered. Then it occurred to me that I was not dealing with a cube at all. I was dealing with a simpler solid, the octahedron. The octahedron has six dimensions (spokes) and seven vertexes.

This gives us a Hauy Construction (this figure is an eight degree):

Using my new taxonomy gives us the following views:

Front:

Side:

Top:

The age of the cube is over. Welcome to the age of the Octahedral Hauy Construction.

Formula

In this context we can deduct the following equation:

In the Business Interpretation E can represent Everything (Monopoly) and M can represent Market.

Generic Table

First, we create the generic table:

Generic Schema

We are now ready to create the schema:

We can also look at the role of long tails (exponential curves) and tipping points (singularities, pluralarities). Singularities occur when the taxonomy reaches it’s cost/benefit optimum and plurality when the data utilizes the entire business space. Benefit declines from that point.

What I am saying here is systems are not tabula rasas. Systems have a hardwired architecture and schematic that obeys simple physical laws that are in many ways understood as well as softwired structure that is unique to the system. We don’t have to create a unique architecture and unique schema for each system. Now they need only to be refined and applied across the spectrum of human endeavor. We need only learn how to classify the data.

I have recently been exposed to a new Intel intranet appliance product called SuiteTwo. SuiteTwo is an integration of MoveableType, SocialText, NewsGator, SimpleFeed, VisiblePath and SpikeSource for the enterprise to take advantage of Blogs, Wikis, Social Networking, RSS feeds, RSS aggregation and Open Source internally. Apparently, eager clients are offering plenty of ideas to even further enhance SuiteTwo and its integrated products, but let’s take a moment to analyze what an ideal tool would ultimately do from the ground up from the perspective of the Six Unities.

Note: the Six Unities are resource groups and resources are both internal and external to the enterprise.

Location – Contact Resources

Locations for each of the entities for each of the unities would be available. I would be able to track the location of staff and inventory according to internal and external coordinates be it geographic, facility, postal, telecom, internet or any other. These are all the enterprise’s touch points. Where are we receiving and transmitting to/from the enterprise? REPOSE. Where the resource contacts.

Trigger – Event Resources

Activations for each of the entities for each of the unities would be available. Ultimately, all events are reactive–dependent on internal or external entities. REFLEX. When the resource contacts.

Data – Product Resources

Inventories of all entities for each of the unities. I would know the quality and quantity of any fixed, virtual and liquid assets of the company according to internal and/or external metrics internally and externally. Data is a repository of all enterprise resources allowing check in and check out. RECORD. What the resource contacts.

Information – Service Resources

Functions performed by all the entities for each of the unities. Whether digital, mechanical or manual all the processes would be documented in human readable form. The work and play done and being done within the enterprise and externally. REPORT. How the resource contacts.

Knowledge – Human Resources

Social Network for all entities for all unities. In every case someone is responsible for every entity internally and externally. Who are we, who do we report to, who do we share with internally and externally? RELATE. Who the resource contacts.

Wisdom – Policy Resources

Meaning and mantra for every entity for every unity. It is important to know the motive of everyone and everything both internally and externally that involves the system in order to know whether they will abide by the greater goal of the enterprise. Why are we united according to internal and external rules? REVISE. Why the resource contacts.

Take a look at the products SuiteTwo integrates and ask yourself if they answer the needs of the six unities. In my opinion SocialText’s Wiki is bearing the brunt of the requirements, but does it stand up? I don’t think it does, because it does not correctly incorporate location, event and inventory.

We concluded that human systems are hexads and we arrived at the Six Hat, Six Coat Framework:

Next, we will look at the Entities, Relationships, Attributes and Constraints within the framework.

Defining the Six Hat, Six Coat Entities has been very much like defining a periodic table. I have had to suspend my own biases many times to align myself with the concepts the Cartesian product were revealing to me.

I have stated that the relationships between entities are one to many left to right and one to many top to bottom. John Zachman believes the structure is like a table with movable columns. I do not. I believe the framework and the entities are fixed in a hierarchy implicitly. However, explicit relationships can exist contrary to this fundamental structure.

We have also explored the attributes for each of the entities and their constraints/freedoms. I provided an alternate set of names: Morality (cause), Compatibility (observer), Reliability (energy), Fidelity (matter), Accessibility (space) and Availability (time).

I will be coming back to the Structured Thinking Language and experiment further.

The important work of moving the world forward does not wait to be done by perfect men.
– George Eliot

In this entry I will explore all of the attributes for all of the entities. This may sound tedious, however, I have found that systematically going through all the combinations reveals modes of thought about the subject matter that I have not before considered.

Recall this diagram:

The real questions the values for the attributes will be answering are: Morality, Compatibility, Reliability, Fidelity, Accessibility, Availability. This will be a long post, but worth the thought.

When I read the Communist Manifesto for the first time I was appalled and remained appalled to this day. I was reading a document of adolescent angst turned into political policy. It was a document of hate, destruction and paranoia.

Observer.Academic.Morality — academic’s liberation of conscience

Observer.Academic.Compatibility — academic’s liberation of governance

Observer.Academic.Reliability — academic’s liberation of profession

Observer.Academic.Fidelity — academic’s liberation of education

Observer.Academic.Accessibility — academic’s liberation of residence

Observer.Academic.Availability — academic’s liberation of existence

Observer.Host.Morality — host’s liberation of conscience

Observer.Host.Compatibility — host’s liberation of governance

Observer.Host.Reliability — host’s liberation of profession

Observer.Host.Fidelity — host’s liberation of education

Observer.Host.Accessibility — host’s liberation of residence

Observer.Host.Availability — host’s liberation of existence

Observer.Regular.Morality — regular’s liberation of conscience

Observer.Regular.Compatibility — regular’s liberation of governance

Observer.Regular.Reliability — regular’s liberation of profession

Observer.Regular.Fidelity — regular’s liberation of education

Observer.Regular.Accessibility — regular’s liberation of residence

Observer.Regular.Availability — regular’s liberation of existence

Energy.Revise.Morality — revision’s liberation of conscience

Energy.Revise.Compatibility — revision’s liberation of governance

Energy.Revise.Reliability — revision’s liberation of profession

Energy.Revise.Fidelity — revision’s liberation of education

Energy.Revise.Accessibility — revision’s liberation of residence

Energy.Revise.Availability — revision’s liberation of existence

Energy.Relate.Morality — relating’s liberation of conscience

Energy.Relate.Compatibility — relating’s liberation of governance

Energy.Relate.Reliability — relating’s liberation of profession

Energy.Relate.Fidelity — relating’s liberation of education

Energy.Relate.Accessibility — relating’s liberation of residence

Energy.Relate.Availability — relating’s liberation of existence

Energy.Report.Morality — reporting’s liberation of conscience

Energy.Report.Compatibility — reporting’s liberation of governance

Energy.Report.Reliability — reporting’s liberation of profession

Energy.Report.Fidelity — reporting’s liberation of education

Energy.Report.Accessibility — reporting’s liberation of residence

Energy.Report.Availability — reporting’s liberation of existence

Energy.Record.Morality — recording’s liberation of conscience

Energy.Record.Compatibility — recording’s liberation of governance

Energy.Record.Reliability — recording’s liberation of profession

Energy.Record.Fidelity — recording’s liberation of education

Energy.Record.Accessibility — recording’s liberation of residence

Energy.Record.Availability — recording’s liberation of existence

Energy.Repose.Morality — reposing’s liberation of conscience

Energy.Repose.Compatibility — reposing’s liberation of governance

Energy.Repose.Reliability — reposing’s liberation of profession

Energy.Repose.Fidelity — reposing’s liberation of education

Energy.Repose.Accessibility — reposing’s liberation of residence

Energy.Repose.Availability — reposing’s liberation of existence

Energy.Regulate.Morality — regulating’s liberation of conscience

Energy.Regulate.Compatibility — regulating’s liberation of governance

Energy.Regulate.Reliability — regulating’s liberation of profession

Energy.Regulate.Fidelity — regulating’s liberation of education

Energy.Regulate.Accessibility — regulating’s liberation of residence

Energy.Regulate.Availability — regulating’s liberation of existence

Matter.Cause.Morality — cause’s liberation of conscience

Matter.Cause.Compatibility — cause’s liberation of governance

Matter.Cause.Reliability — cause’s liberation of profession

Matter.Cause.Fidelity — cause’s liberation of education

Matter.Cause.Accessibility — cause’s liberation of residence

Matter.Cause.Availability — cause’s liberation of existence

Matter.Observer.Morality — observer’s liberation of conscience

Matter.Observer.Compatibility — observer’s liberation of governance

Matter.Observer.Reliability — observer’s liberation of profession

Matter.Observer.Fidelity — observer’s liberation of education

Matter.Observer.Accessibility — observer’s liberation of residence

Matter.Observer.Availability — observer’s liberation of existence

Matter.Energy.Morality — energy’s liberation of conscience

Matter.Energy.Compatibility — energy’s liberation of governance

Matter.Energy.Reliability — energy’s liberation of profession

Matter.Energy.Fidelity — energy’s liberation of education

Matter.Energy.Accessibility — energy’s liberation of residence

Matter.Energy.Availability — energy’s liberation of existence

Matter.Matter.Morality — matter’s liberation of conscience

Matter.Matter.Compatibility — matter’s liberation of governance

Matter.Matter.Reliability — matter’s liberation of profession

Matter.Matter.Fidelity — matter’s liberation of education

Matter.Matter.Accessibility — matter’s liberation of residence

Matter.Matter.Availability — matter’s liberation of existence

Matter.Space.Morality — space’s liberation of conscience

Matter.Space.Compatibility — space’s liberation of governance

Matter.Space.Reliability — space’s liberation of profession

Matter.Space.Fidelity — space’s liberation of education

Matter.Space.Accessibility — space’s liberation of residence

Matter.Space.Availability — space’s liberation of existence

Matter.Time.Morality — time’s liberation of conscience

Matter.Time.Compatibility — time’s liberation of governance

Matter.Time.Reliability — time’s liberation of profession

Matter.Time.Fidelity — time’s liberation of education

Matter.Time.Accessibility — time’s liberation of residence

Matter.Time.Availability — time’s liberation of existence

Space.Universal.Morality — universe’s liberation of conscience

Space.Universal.Compatibility — universe’s liberation of governance

Space.Universal.Reliability — universe’s liberation of profession

Space.Universal.Fidelity — universe’s liberation of education

Space.Universal.Accessibility — universe’s liberation of residence

Space.Universal.Availability — universe’s liberation of existence

Space.Global.Morality — globe’s liberation of conscience

Space.Global.Compatibility — globe’s liberation of governance

Space.Global.Reliability — globe’s liberation of profession

Space.Global.Fidelity — globe’s liberation of education

Space.Global.Accessibility — globe’s liberation of residence

Space.Global.Availability — globe’s liberation of existence

Space.Commercial.Morality — market’s liberation of conscience

Space.Commercial.Compatibility — market’s liberation of governance

Space.Commercial.Reliability — market’s liberation of profession

Space.Commercial.Fidelity — market’s liberation of education

Space.Commercial.Accessibility — market’s liberation of residence

Space.Commercial.Availability — market’s liberation of existence

Space.Collegial.Morality — campus’s liberation of conscience

Space.Collegial.Compatibility — campus’s liberation of governance

Space.Collegial.Reliability — campus’s liberation of profession

Space.Collegial.Fidelity — campus’s liberation of education

Space.Collegial.Accessibility — campus’s liberation of residence

Space.Collegial.Availability — campus’s liberation of existence

Space.Habitual.Morality — habitat’s liberation of conscience

Space.Habitual.Compatibility — habitat’s liberation of governance

Space.Habitual.Reliability — habitat’s liberation of profession

Space.Habitual.Fidelity — habitat’s liberation of education

Space.Habitual.Accessibility — habitat’s liberation of residence

Space.Habitual.Availability — habitat’s liberation of existence

Space.Chronal.Morality — physiology’s liberation of conscience

Space.Chronal.Compatibility — physiology’s liberation of governance

Space.Chronal.Reliability — physiology’s liberation of profession

Space.Chronal.Fidelity — physiology’s liberation of education

Space.Chronal.Accessibility — physiology’s liberation of residence

Space.Chronal.Availability — physiology’s liberation of existence

Time.Year.Morality — solar cycle’s liberation of conscience

Time.Year.Compatibility — solar cycle’s liberation of governance

Time.Year.Reliability — solar cycle’s liberation of profession

Time.Year.Fidelity — solar cycle’s liberation of education

Time.Year.Accessibility — solar cycle’s liberation of residence

Time.Year.Availability — solar cycle’s liberation of existence

Time.Month.Morality — lunar cycle’s liberation of conscience

Time.Month.Compatibility — lunar cycle’s liberation of governance

Time.Month.Reliability — lunar cycle’s liberation of profession

Time.Month.Fidelity — lunar cycle’s liberation of education

Time.Month.Accessibility — lunar cycle’s liberation of residence

Time.Month.Availability — lunar cycle’s liberation of existence

Time.Day.Morality — circadian cycle’s liberation of conscience

Time.Day.Compatibility — circadian cycle’s liberation of governance

Time.Day.Reliability — circadian cycle’s liberation of profession

Time.Day.Fidelity — circadian cycle’s liberation of education

Time.Day.Accessibility — circadian cycle’s liberation of residence

Time.Day.Availability — circadian cycle’s liberation of existence

Time.Hour.Morality — hourly cycle’s liberation of conscience

Time.Hour.Compatibility — hourly cycle’s liberation of governance

Time.Hour.Reliability — hourly cycle’s liberation of profession

Time.Hour.Fidelity — hourly cycle’s liberation of education

Time.Hour.Accessibility — hourly cycle’s liberation of residence

Time.Hour.Availability — hourly cycle’s liberation of existence

Time.Minute.Morality — minuta cycle’s liberation of conscience

Time.Minute.Compatibility — minuta cycle’s liberation of governance

Time.Minute.Reliability — minuta cycle’s liberation of profession

Time.Minute.Fidelity — minuta cycle’s liberation of education

Time.Minute.Accessibility — minuta cycle’s liberation of residence

Time.Minute.Availability — minuta cycle’s liberation of existence

Time.Second.Morality — secunda cycle’s liberation of conscience

Time.Second.Compatibility — secunda cycle’s liberation of governance

Time.Second.Reliability — secunda cycle’s liberation of profession

Time.Second.Fidelity — secunda cycle’s liberation of education

Time.Second.Accessibility — secunda cycle’s liberation of residence

Time.Second.Availability — secunda cycle’s liberation of existence

Well, that was a long haul, but we now have a periodic table for systems. I suggest that you print this out and reflect on each of the sections. Even though the world appears to be a difficult place, we are continually as a species gaining greater and greater liberties. And every aspect of systems are contributing to that.

I have recently crossed paths with David Bryson M.D. and through our discussions he brought to my attention an article he felt complements my work

Physical: Regulate, Repose

Decisional: Record, Report

Perceptual: Relate, Revise

and which with his permission I am reproducing here. Dr. Bryson is currently working on a concept he intends to present during the 2009 celebration of the 200th anniversary of Darwin’s publication of Evolution of the Species. –Grant Czerepak

Theories of mammalian learning and theories of mammalian sleep have developed with scant interaction. This article states that mammalian sleep and learning are related fundamentally. Our approach is theoretical; no new experimental data are presented. Aspects of human behavior which are distinct from those of mammals in general will not be considered here.

Synopsis

Much of the mature mammal’s behavior is devoid of any significant decision making, due to the familiarity of most of the inputs with which the mature mammal deals. Familiar inputs are associated with the execution of routine behavioral acts, and during such periods mammalian record keeping is insignificant. In contrast, the record of the mammal’s activities which is kept is directly related to episodes of decision making. A decision is made when the mammal is confronted with an unfamiliar input, and this input, the resulting decision, and the outcome of the decision are recorded. For example, a hungry mammal may suspect that some unfamiliar substance is edible, may decide to sample it, and may find the taste unacceptable. This input, this decision, and this consequence are recorded.

The decisional record thus grows as the waking state progresses, at a rate related to the frequency of unfamiliar inputs. The decision record may be accessed as soon as a decision and its consequences have occurred, enabling a mammal to learn within a single waking period. Should some unfamiliar input recur, the current need for decision making may be reduced considerably if the previous decision for the same input had and acceptable consequence. If not, the probability of invocking this decision again is decreased, and decision making yields another decision and perhaps a more acceptable consequence.

Learning of this type is inadequate in one important respect. Access to the decisional record is limited to one decisional cluster (unfamiliar input, decision, consequence) at a time; decisional clusters are not themselves compared. For those inputs which do recur, the original problem of input unfamiliarity is improved empirically on a case-by-case basis. However, improved decision making for each case still fails to exploit any generic relationships which may exist between the individual decisional clusters.

During sleep, the information in the decisional record is utilized for a further purpose. The individual decisional clusters are combined into informational sets, the combinatorial rule being to group those unfamiliar inputs in which the decisions and consequences were similar. For example, suppose a mammal in an unfamiliar environment has spent various portions of the current waking state in trying to establish reliable landmarks for navigational purposes. During sleep, those environmental features which were selected to be–and in fact turned out to be–reliable landmarks are grouped into one informational set. Inductive analysis of this set of unfamiliar inputs may reveal recurrent similarities in their characteristics, a finding with implications for the input classification (perceptual) system. If so, the perceptual system is revised as the mammal sleeps. Sleep thus enables the mammal to classify unfamiliar inputs having the same significance as the same perception. Thus previously unfamiliar inputs subsequently are perceived with increased familiarity.

Two categories of mammalian learning are thus proposed: decisional learning, a waking activity in which output selection for the same input is improved; and perceptual learning, a sleeping activity in which the functional reorganization of input classes reduces the number of decisional involvements required previously. Decisional learning is akin to “stimulus-response” learning; perceptual learning is akin to “gestalt” learning. All perceptual learning is the result of recent decisional learning. When the inputs associated with a series of decisions with inadequate consequences can be related and thus lead to perceputal learning, a considerable behavioral advancement may occur from one waking state to the next.

The first section of the article develops a model of the informational operations between initial input (attention) and final output (manifest behavior). The model describes how decisional learning and perceptual learning are related to the overall control of behavior. The setting of the model is ethological. The second section confronts learning research in the laboratory setting. The research section is referenced; the model section is not.

The Model

The model is presented at the level of a simple behavioral analysis. Our prototype mammal is always in one of two output modes when interacting with the environment: decision making, or decision execution. During decision making, the mammal is obviously inspecting or choosing; during decison execution, the mammal is obviously operating on the environment as part of some goal-directed act. Decison making and decison execution are to us thus a matter of seconds rather than milliseconds.

Two sequential processes are invovled on the input side of mammalian behavior: attention (input sampling) and perception (input classification). Attention and perception are components of both decision making and decison execution. The sequence of attention-perception-output-attention-perception-output may thus represent either ongoing decision making or ongoing decision execution.

We classify input into three types: potential input, attended input, and perceived intput. The process of perception converts attended input into perceived input.

Potential input is the totality of the physical environment to which the mammal theoretically may attend at any time. Potential input is thus a range of input information, reflecting the theoretical limits of the mammal’s sensory equipment. Attended input is that constellation of physical variables (light, sound, chemical concentration, etc.) to which the mammal actually attends at any time. The dimensions of potential input and attended input are always physical. During decison execution, the dimensions of perceived input becomes those of the utility and survival of a particular mammal at a particular time.

During decision execution (peeling a fruit, copulating, grooming), the mammal actively attends to its own behavioral output and in so doing excludes the remainder of potential input. Attended inputs here are thus an extremely narrow and gradually shifting sample of potential input. As long as attended inputs remain within prescribed tolerances, decision execution continues toward completion with no interruption for decision making.

Decision execution may be interrupted by sudden changes in potential input (as sudden noise or shadow). Attention automatically is diverted from behavioral monitoring. If the environmental change, now represented in attended input, is perceived as obviously irrelevant to the mammal (as a familiar “false alarm”), attention is returned to consummating the current goal. If the change is perceived as obviously relevant (a familiar opportunity or danger of greater significance than the current activity), the mammal quickly decides upon the more appropriate behavioral act and devotes its attention to the execution of this decision rather than the previous decision.

When the relevance of attended input is not immediately apparent, the mammal switches to the decision making mode. During decision making, attention is determined by a complex interaction between the mammal and its environment. The mammal attends to increasingly diverse aspects of potential input, making active searches for suspected environmental features and also being passively drawn to unexpected environmental features, and continues to do so until it discovers or is confronted with some environmental feature of obvious relevance. The mammal then returns to the decision-execution mode.

Every attended input is transformed into a perceived input. The product of perception is a perceived input of variable familiarity. Perceived inputs of high familiarity are perceived as action oriented (output oriented) and are associated with ongoing decision execution or the initiation of decision execution. Perceived inputs of low familiarity are perceived as feature oriented (input oriented) and are associated with ongoing decision making or the initiation of decision making.

During decision execution, two mammals may attend to similar features of the environment but have quite different perceptions. For example, suppose two mammals are attending to certain physical features of an edible plant which only grows near an open water source. Attended input A of mammal A is very similar to attended input B of mammal B. However, perceived input A is high in a dimension reflecting the accessibility of food, which mammal A happens to be looking for, while perceived input B is high in a dimension reflecting the accessibility of water, which mammal B happens to be looking for. During decision execution, perception reflects the current functiona requirements of the mammal. During decison making, because of the difficulty in classifying unfamiliar attended inputs, perception reflects the more constant structural features of physical reality.

On the output side of the model, every perceived input is transformed into an output signal. During execution, the output signal furthers the behavioral action represented in the precediing perceived input. During decison making, the output signal is related to obtaining more information relevant to the precedinng perceived input. During both output modes, the output signal directs attention in relation to the formation of the next attended input.

Within a single waking state, decision making results in decisional learning. Decisional learning can directly reduce the duration of subsequent decision-making episodes, and can indirectly reduce the number of subsequent decision-making episodes by improving the quality of decision making. During sleep, decisional learning results in perceptual learning. Perceptual learning can directly improve decision execution by improving input classification, thereby reducing the number of unnecessary interruptions. Perceptual learning sets the tolerances for variation in inputs at a functional level. Improved decison execution thus directly reduces the number of decision-making episodes.

Wide variations exist for the relative role of perceptual learning among different mammalian classes. Rodents are born with a number of input classes already fixed, and relatively few input classes are added as life proceeds. Rodents are nearly always in the decision-execution mode, since they have so few behavioral acts to decide between, and since their tolerance for input variation during decision execution is relatively broad. Most of the input classes of primates are learned, and the complex behavior of an adult primate requires a considerable repetoire of pereceptual categories. Primates are often in the decision making mode, since they have so many behavioral acts to decide between, and since their tolerance for input variation during decision execution is relatively narrow.

Such variation is related to the phenomena of play and curiosity. These are common features of primate behavior, especially during development, and are virtually absent from rodent behavior. We consider play and curiosity as phenomena which maximize decison making. Increased decision making leads to increased decisional learning, decisional learning to perceptual learnining, and perceptual learning to improved decision execution. As a result of play and curiosity, the behavioral repetoire of a mammal is increased, and thereby future waking-state activities which now have a goal-fulfilling function may be performed more effectively.

Implications for Research

Our model suggests that the unusual interaction of decisional learning and perceptual learning results in gradual, quantitative improvements in mammalian performance. For behavioral acts of which the mammal is already capable, improved output selection can simulate revised input classification before the latter occurs. Therefore sleep is not required for quantitative improvement in performance.

In order to demonstrate the role of sleep in mammalian learning criterion performance should represent a qualitative improvement over current performance. Such performance corresponds to the “problem-solving” class of previous experiments. While perceptual learning usually results in the modification of a previous input class, problem-solving behavior requires the formation of a new input class corresponding to the problem solution. We thus consider problem solving as a special case of perceptual learning. Since a new input class is required, decisional learning cannot simulate perceptual learning, allowing the role of sleep to be tested.

That sleep is not required for quantitative improvements in performance is obvious from experiments showing improved performance from the first trial outward [1]. We analyze such performance as improved output selection for the same perceived input (decisional learning). That sleep is required for qualitative improvements in performance is not obvious from previous research. To our knowledge, no experiment in mammalian problem solving has studied sleep as a performance variable. The following analyses of previous experiments are therefore inferential.

Chimps which did not use a hoe to reach for food placed outside their cages did so “three days later,” after intervening ad lib experience with sticks [2]. We suggest that primate curiosity resulted in the formation of a new input class in which sticks became perceived as a functional extension of the arm. A de novo decision execution thereby was made possible when the chimps were reconfronted with the original situation.

The “learning to learn” experiments with primates all take more than one training session [3]; improvement within a single training session is negligible [4]. We suggest that such experiments can also be explained as a special case of perceptual learning, with the problem solution representing a new input classification.

The perception of “size constancy” (learning that stimulus properties are distance invariant) takes about ten days for rats previously reared in darkness [5]. While not a classic problem-solving paradigm, we suggest that here again the formation of a new perceptual category was based on recent decisional learning, and the intervening sleep was a necessity.

Dogs and cats were trained to move around and behind a screen on the side to which food disappeared [6]. The problem here is to learn that the same food continues to exist after visual representation of the food is no longer a part of attended input. No animal achieved problem solution (moving to the side of the food, sometimes to the right, sometimes to the left) on the first of daily training sessions. Furthermore, in the data as published, problem solution tended to appear on the first trial of a daily session (presumably the only trial after intervening sleep). We suggest that intervening sleep was, in fact, required for criterion performance. Before solution, both dogs and cats exhibited “position habits,” that is, always choosing the same route (for some always the left, for others always the right), resulting in 50 percent rewarded trials for chance alone. We suggest that high chance-based reward rates tend to preserve a decisional basis for behavior, and thus that decreasing the incidence of chance-based payoff will accelerate the appearance of problem solution.

Because sleep has been neglected variable in problem-solving experiments, the first trial of a daily training session usually has had two features which must be dissociated: it is usually only trial which follows sleep, and it is usually the trial which ends the longest intertrial interval. When waking time and sleeping time are equated, we predict that normal sleep is more favorable to problem solution than is any waking activity of equal duration, including continued exposure to a problem. Furthermore, we predict that in problem-solving experiments, as the above examples, criterion performance cannot be established in the first training session (no intervening sleep) regardless of the number of trials within the first training sessions. However, compression of trials within a few training session, as opposed to the same number of trials distributed over many training sessions, should favor the apperance of problem solution. Compression of relevant trials favors inductive operations in the following sleep state.

All decisional learning is time based (the cotemporality of unfamiliar input, decision and consequence within a decisional cluster). In the informational rearrangements of sleep, temporal relationships within a decisional cluster are reduced, and categorical relationships between decisional clusters are enhanced (perceptual learning). Since our model assigns decisional learning to a given waking state, we cannot rigorously approach the effect of sleep on decisional learning. We do suggest that the more a performance represents a unique temporal association devoid of significant implications for input classification, the more that intervening sleep will revert this performance toward the prelearning level. We therefore suggest that time-based performance is better retained by distributing a given trial over many training sessions, as opposed to compressing the same number of trials within a few training sessions.

A general finding for all mammals is a decrease in sleep as life proceeds[7]. In terms of our model, increasing comprehensiveness of input classification increases input familiarity, increased input familiarity reduces decision making, reduced decision making reduces new record keeping, and reduced record keeping reduces the informational rearrangements of sleep. We thus suggest that an unfamiliar environment should cause increased sleep, regardless of the age of the mammal. In particular, we suggest that “sensory deprivation” is familiar to a newborn and thus should cause decreased subsequent sleep, while sensory deprivation is unfamiliar to an adult mammal and thus should cause increased subsequent sleep.

Mammalian sleep is composed of alternating periods of low and high brain metabolism [8]. We speculate that sleep is a recurrent ABABAB phenomenon in which an A period (low metabolism) is a necessary preparation for the following B period (high metabolism). If true, specifically depriving a mammal of B periods (rapid eye movement sleep deprivation) should interfere with recent learning more than total sleep deprivation, even though the latter is of greater clock time.

We repeat what we think is the most important implication of our model for future research. Problem-solving learning is a special case of perceptual learning. We predict that normal sleep is more favorable to problem solution in mammals than is any waking activity of equal duration, including continued exposure to the problem.